Hepatocellular Carcinoma-Associated Gene

ABSTRACT

The present invention provides a method for evaluating cancer, which comprises the following steps of:
     (a) collecting total RNA from an analyte;   (b) measuring the expression level of at least one gene selected from among the genes shown in Tables 1 to 8; and   (c) evaluating cancer using the measurement result as an indicator.

TECHNICAL FIELD

The present invention relates to a gene associated with hepatocellularcarcinoma, and particularly to a gene associated with the recurrence ofhepatocellular carcinoma.

BACKGROUND ART

Almost all types of hepatocellular carcinomas are developed from chronichepatitis caused by viral hepatitis. The causal viruses thereof arehepatitis C virus and hepatitis B virus. If a patient is persistentlyinfected with either hepatitis C virus or hepatitis B virus, there areno therapeutic methods therefor. The patient does nothing but onlyfacing a fear of developing liver cirrhosis or hepatocellular carcinoma.Interferon has been used as an agent for treating hepatitis. However,effective examples are only 30%, and thus this is not necessarily asufficient therapeutic agent. Under the present circumstances, there arealmost no effective examples, in particular, for chronic hepatitis.Nevertheless, even if such viruses cannot be eliminated, if progressionof pathologic conditions can be suppressed, it leads to prevention ofliver cirrhosis or hepatocellular carcinoma. Thus, it is consideredimportant to clarify the factor of developing pathologic conditions at amolecular level.

If once hepatocellular carcinoma has been developed, even if a surgicalradical operation is made, the recurrence of cancer in the remainingliver appears at a high frequency. The survival rate obtained 5 yearsafter the operation of liver cancer is 51% on a national accumulationbase. It has been reported that such recurrence appears at approximately25% of cases 1 year after hepatectomy, at 50% thereof 2 years afterhepatectomy, and at 80% thereof 5 years after hepatectomy. Hence, itcannot be said that remaining liver tissues are normal liver tissues,but it is considered that a bud of the recurrence of hepatocellularcarcinoma has already existed. At present, it has been reported thatrecurrence risk factors include the maximum diameter of a tumor, thenumber of tumors, tumor embolus of portal vein, a preoperative AFPvalue, intrahepatic metastasis, the presence or absence of livercirrhosis, etc. However, in order to develop a method for predicting andpreventing the recurrence of hepatocellular carcinoma, it is necessaryto find at a molecular level a factor of determining the presence orabsence of recurrence, which is associated with such risk factors. Sucha factor obtained at a molecular level is considered to be a factor,which is associated not only with recurrence but also with thedevelopment of hepatocellular carcinoma or progression of pathologicconditions. In recent years, as a result of gene expression analysisusing a DNA microarray, it has become possible to classify more indetail such pathologic conditions based on the difference in theexpression patterns of genes as a whole. To date, histological orimmunological means have been mainly used for classification of cancers.However, cancers classified into the same type have different clinicalcourses and therapeutic effects depending on individual cases. If therewere a means for classifying such cancers more in detail, it wouldbecome possible to offer treatment depending on individual cases. It isconsidered that the gene expression analysis using a DNA microarrayconstitutes a powerful method for knowing the prognosis of such cancers.

To date, the DNA microarray analysis has clarified the following pointsassociated with hepatocellular carcinoma:

(i) the types of genes, the expressions of which are different between atumor tissue and a nontumor tissue (Shirota Y, Kaneko S, Honda M, et al.Identification of differentially expressed gene in hepatocellularcarcinoma with cDNA microarrays. Hepatology 2001; 33: 832-840, Xu X,Huang J, Xu Z, et al. Insight into hepatocellular carcinogenesis attranscriptome level by comparing gene expression profiles ofhepatocellular carcinoma with those of corresponding noncancerous liver.Proc. Nat. Acad. Sci. USA. 2001; 98: 15089-15094);(ii) in terms of the differentiation degree of cancer tissues, the typesof genes, the expressions of which are different (Shirota Y, Kaneko S,Honda M, et al. Identification of differentially expressed gene inhepatocellular carcinoma with cDNA microarrays. Hepatology 2001; 33:832-840, Okabe H, Satoh S, Kato T, et al. Genome-wide analysis of geneexpression in human hepatocellular carcinomas using cDNA microarray:Identification of genes involved in viral carcinogenesis and tumorprogression. Cancer res. 2001; 61: 2129-2137);(iii) the types of genes, the expressions of which are different betweenhepatocellular carcinoma derived from hepatitis B and hepatocellularcarcinoma derived from hepatitis C (Okabe H, Satoh S, Kato T, et al.Genome-wide analysis of gene expression in human hepatocellularcarcinomas using cDNA microarray: Identification of genes involved inviral carcinogenesis and tumor progression. Cancer res. 2001; 61:2129-2137);(iv) the types of genes, the expressions of which are differentdepending on the presence or absence of vascular invasion ofhepatocellular carcinoma (Okabe H, Satoh S, Kato T, et al. Genome-wideanalysis of gene expression in human hepatocellular carcinomas usingcDNA microarray: Identification of genes involved in viralcarcinogenesis and tumor progression. Cancer res. 2001; 61: 2129-2137);and(v) the type of a change in gene expression observed among intrahepaticmetastatic cancers, as a result of the clonal analysis of multinodularhepatocellular carcinoma (Cheung S, Chen X, Guan X, et al. Identifymetastasis-associated gene in hepatocellular carcinoma through clonalitydelineation for multinodular tumor. Cancer res. 2002; 62: 4711-4721).

However, with regard to genes associated with recurrence, only theanalysis of Iizuka et al. on cancer tissues has existed (Iizuka N, OkaM, Yamada-Okabe H, et al. Oligonucleotide microarray for prediction ofearly intrahepatic recurrence of hepatocellular carcinoma after curativeresection. Lancet 2003; 361: 923-929). The analysis of nontumor livertissues, which reflects the remaining liver tissues, has not yet beenachieved.

DISCLOSURE OF THE INVENTION

It is an object of the present invention to provide a gene associatedwith hepatocellular carcinoma, and particularly, a gene, which predictsthe recurrence of the cancer.

As a result of intensive studies directed towards achieving theaforementioned object, the present inventor has studied the profile ofgene expression based on a case where hepatocellular carcinoma hasrecurred and a case where hepatocellular carcinoma has not recurred, andhas succeeded in identification of a gene associated with hepatocellularcarcinoma, thereby completing the present invention.

That is to say, the present invention has the following features:

(1) A method for evaluating cancer, which comprises the following stepsof:(a) collecting total RNA from an analyte;(b) measuring the expression level of at least one gene selected fromamong the genes shown in Tables 1 to 8; and(c) evaluating cancer using the measurement result as an indicator.

In the present invention, from among the genes shown in Tables 1 to 8,at least one gene selected from the group consisting of the PSMB8 gene,the RALGDS gene, the GBP1 gene, the RPS14 gene, the CXCL9 gene, theDKFZp564F212 gene, the CYP1B1 gene, the TNFSF10 gene, the NROB2 gene,the MAFB gene, the BF530535 gene, the MRPL24 gene, the QPRT gene, theVNN1 gene, and the IRS2 gene, can be used, for example. Otherwise, fromamong the genes shown in Tables 1 to 8, at least one gene selected fromthe group consisting of the PZP gene, the MAP3K5 gene, the TNFSF14 gene,the LMNA gene, the CYP1A1 gene, and the IGFBP3 gene, can be used, forexample.

In addition, when such measurement is carried out using GAPDH as aninternal standard gene, from among the genes shown in Tables 1 to 8,each gene contained in a gene set consisting of the VNN1 gene and theMRPL24 gene, or a gene set consisting of the PRODH gene, the LMNA gene,and the MAP3K12 gene, can be used.

Moreover, when such measurement is carried out using 18S rRNA as aninternal standard gene, from among the genes shown in Tables 1 to 8,each gene contained in a gene set consisting of the VNN1 gene, the CXCL9gene, the GBP1 gene, and the RALGDS gene, or a gene set consisting ofthe LMNA gene, the LTBP2 gene, the COL1A2 gene, and the PZP gene, can beused.

The above evaluation of cancer involves prediction of the presence orabsence of metastasis or recurrence. Further, an example of such canceris hepatocellular carcinoma.

The expression level of a gene can be measured by amplifying the gene,using at least one set of primers consisting of the nucleotide sequencesshown in SEQ ID NOS: 2n−1 and 2n (wherein n represents an integerbetween 1 and 114). Otherwise, the expression level of a gene can bemeasured by amplifying the gene, using a set of primers for amplifyingeach gene contained in at least one gene set selected from the groupconsisting of a gene set consisting of the VNN1 gene and the MRPL24gene, a gene set consisting of the PRODH gene, the LMNA gene, and theMAP3K12 gene, a gene set consisting of the VNN1 gene, the CXCL9 gene,the GBP1 gene, and the RALGDS gene, and a gene set consisting of theLMNA gene, the LTBP2 gene, the COL1A2 gene, and the PZP gene.

(2) A primer set, which comprises at least one set of primers consistingof the nucleotide sequences shown in SEQ ID NOS: 2n−1 and 2n (wherein nrepresents an integer between 1 and 114).(3) A primer set, which comprises a set of primers for amplifying eachgene contained in at least one gene set selected from the groupconsisting of a gene set consisting of the VNN1 gene and the MRPL24gene, a gene set consisting of the PRODH gene, the LMNA gene, and theMAP3K12 gene, a gene set consisting of the VNN1 gene, the CXCL9 gene,the GBP1 gene, and the RALGDS gene, and a gene set consisting of theLMNA gene, the LTBP2 gene, the COL1A2 gene, and the PZP gene.(4) A kit for evaluating cancer, which comprises any gene shown inTables 1 to 8.

An example of the aforementioned gene is at least one gene selected fromthe group consisting of the RALGDS gene, the GBP1 gene, the DKFZp564F212gene, the TNFSF10 gene, and the QPRT gene.

Moreover, another example of the aforementioned gene is each genecontained in at least one gene set selected from the group consisting ofa gene set consisting of the VNN1 gene and the MRPL24 gene, a gene setconsisting of the PRODH gene, the LMNA gene, and the MAP3K12 gene, agene set consisting of the VNN1 gene, the CXCL9 gene, the GBP1 gene, andthe RALGDS gene, and a gene set consisting of the LMNA gene, the LTBP2gene, the COL1A2 gene, and the PZP gene.

Furthermore, the kit of the present invention may comprise theaforementioned primer set.

The present invention provides a gene useful for predicting therecurrence of hepatocellular carcinoma. Cancer can be evaluated byanalyzing the increased expression state of such a gene. In particular,using the gene of the present invention, the recurrence ofhepatocellular carcinoma can be predicted, and the obtained predictioninformation is useful for the subsequent therapeutic strategy. Moreover,the use of such a gene and a gene product enables the development of atreatment method for preventing recurrence.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a view showing the phylogenetic tree of samples obtained fromthe entire gene expression profile. Genes are rearranged based on thesimilarity in expression manner among samples, and further, samples arerearranged based on the similarity in the expression manner of theentire genes. Thus, the genetic affiliation is expressed in the form ofa phylogenetic tree.

BEST MODE FOR CARRYING OUT THE INVENTION

The present invention will be described in detail below.

The present invention is characterized in that the follow-up clinicaldata collected for a long period of time after the resection ofhepatocellular carcinoma are divided into a poor prognosis case group(for example, a case group wherein the cancer recurs within 1 year,leading to death within 2 years) and into a good prognosis case group(for example, a case group wherein the cancer does not recur for 4 ormore years), and is characterized in that a gene causing poor prognosisor a gene causing good prognosis (for example, a gene associated withpromotion of the recurrence and a gene associated with suppression ofthe recurrence) is identified based on the characteristics of a genegroup, which is expressed in the excised liver tissues. The presentinvention relates to classification of causal viruses into type Bhepatocellular carcinoma cases and into type C hepatocellular carcinomacases based on clinical data, and identification of a gene having aprognostic correlation from each of the tissues of a nontumor tissue andthe tissues of a tumor tissue.

The gene of the present invention is obtained by analyzing thecorrelation between tissues actually collected from a patient and apathologic condition thereof, and thereby clarifying the type of a case,a pathologic condition, and a gene, which are used to clarify thecorrelation between a gene and a pathologic condition.

1. Classification of Test Samples

The postoperative course is observed after an operation to resect livercancer, and test samples are classified into an early recurrence groupand into a late recurrence group.

The term “early recurrence group” is used to mean a case group whereinthe cancer recurs within a certain period of time after resection,thereafter leading to death. A recurrence period is not particularlylimited. For example, it is 1 year or shorter, or 2 years or shorter. Asurvival time is not particularly limited either. For example, it is 1year or shorter, 2 years or shorter, or 3 years or shorter, afterrecurrence. The term “late recurrence group” is used to mean a casegroup wherein the cancer does not recur for a certain period of timeafter resection (for example, 3 years or longer, and preferably 4 yearsor longer).

In reality, 51 cases, which were subjected to an operation to resecthepatocellular carcinoma at stages I and II, were used as targets. The51 cases contain 16 cases of type B hepatocellular carcinoma and 35cases of type C hepatocellular carcinoma. Based on the follow-upclinical data of such cases, 2 cases were selected from the type Bhepatocellular carcinoma and 3 cases were selected from the type Chepatocellular carcinoma, and these cases were classified into an earlyrecurrence group. On the other hand, 2 cases selected from the type Bhepatocellular carcinoma and 3 cases were selected from the type Chepatocellular carcinoma, and these cases were classified into a laterecurrence group. With regard to the RNA portions of the nontumortissues and tumor tissues of such 10 cases, the following expressionprofile analysis was carried out.

2. Gene Analysis

Total RNA is extracted from each type of the liver tissues of theclassified groups, and gene expression profiles are then comparedbetween the groups using a microarray. Such total RNA can be extractedusing a commercially available reagent (for example, TRIzol). Fordetection of an expression profile, Microarray (Affymetrix) is used, forexample.

Moreover, the present invention enables the analysis of a gene, whichchanges expression in the tissues of a nontumor tissue as well as in thetissue of a tumor tissue. The term “nontumor tissue” is used herein tomean liver tissues involved in a resection of hepatocellular carcinoma,which do not contain cancer cells. However, such a “nontumor tissue”does not necessarily mean normal liver tissues, but it also includestissues affected by chronic hepatitis (hepatitis B or hepatitis C) orliver cirrhosis. For example, a gene up-regulated in a nontumor tissuein a late recurrence group including type B hepatocellular carcinomacases or type C hepatocellular carcinoma cases, wherein almost alltissues are such affected tissues, can be used as an analysis target. Inthe case of such tissues affected by chronic hepatitis or livercirrhosis, a necrotic inflammatory reaction, regenerating nodules,fibrosis attended with decidual liver cells, or the like are observed.Among such cells, there are cells, which can be potential cells causingthe development of hepatocellular carcinoma. Accordingly, it isconsidered that gene expression relevant to prognosis exists in thenontumor tissue. Thus, prognosis (for example, recurrence) can bepredicted using such gene expression as an indicator (for example, byanalyzing changes in such gene expression).

A gene used for evaluation of cancer is identified based on thecorrelation of changes in gene expression with phenotype (recurrence,early progression, etc.). The term “evaluation of cancer” is used tomean evaluation regarding the pathologic conditions of cancer or thestage of cancer progression. Such evaluation of cancer includesprediction of the presence or absence of metastasis or recurrence.

The present invention provides an up-regulated gene or a down-regulatedgene in terms of recurrence. The term “recurrence” is used to mean thata lesion, which is considered to be a new carcinoma, appears in theliver, after a treatment for a primary lesion has been determined tocomplete.

3. Evaluation of Gene

Using disease model cells or animals, the identified gene is evaluatedin terms of availability as a factor of suppressing the development ofpathologic conditions. Namely, (1) the remaining cases of hepatocellularcarcinoma, the prognosis of which has been known, are subjected toquantitative analysis of gene expression, and the correlation with theprognosis is studied. (2) The gene is transferred into a hepatocellularcarcinoma-cultured cell line, and it is allowed to express therein.Thereafter, the cell growth and a change in malignancy are evaluatedbased on ability to form colonies in a soft agar plate or ability toform tumors in nude mice. (3) Using a cultured hepatic cell lineestablished from a patient with chronic hepatitis, the gene istransferred into the cells, and it is allowed to express therein.Thereafter, the cell growth and malignant transformation are evaluatedby the same method as that described in (2) above. (4) The gene istransferred into the liver of a hepatocellular carcinomadevelopment-model animal, and it is allowed to express therein.Thereafter, the course up to the development of liver cancer isevaluated.

In (1) above, the quantitative analysis of gene expression is carriedout by real-time PCR, for example. That is to say, a commerciallyavailable reverse transcriptase is used for the total RNA as producedabove, so as to synthesize cDNA. As a PCR reagent, a commerciallyavailable reagent can be used. Moreover, PCR may be carried out inaccordance with commercially available protocols. For example,preliminary heating is carried out at 95° C. for 10 minutes, andthereafter, a cycle consisting of 95° C. for 15 seconds and 60° C. (or65° C.) for 60 seconds, is repeated 40 times. Examples of an internalstandard gene used herein as a target may include housekeeping genessuch as glyceraldehyde 3-phosphatase dehydrogenase (GAPDH), 18Sribosomal RNA (18S rRNA), β-Actin, cyclophilin A, HPRT1 (hypoxanthinephosphoribosyltransferase 1), B2M (beta-2 microglobulin), ribosomalprotein L13a, or ribosomal protein L4. Persons skilled in the art canappropriately select such an internal standard gene. As an analysismethod, absolute quantitative analysis or relative quantitative analysisof an expression level is adopted. The absolute quantitative analysis ispreferable. Herein, absolute quantification of an expression level isobtained by determining a threshold line on which a calibration curvebecomes optimum and then obtaining the number of threshold PCR cyclesand a threshold cycle value (Ct) of each sample. On the other hand, arelative expression level is expressed with a Δ Ct value obtained bysubtracting the Ct value of an internal standard gene (for example,GAPDH) from the Ct value of a target gene. Values obtained using theformula (2(^(−ΔCt))) can be used for evaluation of a linear expressionlevel.

When a calibration curve is produced, values obtained by subjectingstandard samples to serial dilution and simultaneous measurement (thesamples are placed in a single plate and simultaneously measured, usinga single reaction solution) may be used.

When an absolute expression level can be obtained relative to acalibration curve, the absolute expression level of a target gene andthat of an internal standard gene are obtained, and the ratio of thetarget gene expression level/the internal standard gene expression levelis calculated for each sample, so as to use it for evaluation.

Genes are selected from the results of the microarray of a laterecurrence group and that of an early recurrence group. Thereafter,among genes, regarding which the results of real-time PCR obtained bythe aforementioned method correspond with the results of the microarray,those exhibiting a correlation with a recurrence period can beidentified as up-regulated genes of nontumor tissue, for example.

As described above, as genes identified as an up-regulated gene, variousgenes can be selected depending on experimental conditions appliedduring the identification, such as an internal standard gene, a primersequence, or an annealing temperature which are used. Also, usingvarious types of statistical methods (for example, Mann-Whitney U test),a gene correlating to a recurrence period can be selected.

The full-length sequence of the gene of the present invention can beobtained as follows. That is to say, it is searched through DNAdatabase, and it can be obtained as known sequence information.Otherwise, the above full-length sequence is isolated from human livercDNA library by hybridization screening.

In the present invention, genes up-regulated in cases where the cancerhas not recurred at an early date (late recurrence) include those shownin Tables 1 to 4. On the other hand, genes up-regulated in cases wherethe cancer has recurred at an early date include those shown in Tables 5to 8.

Table 1: Genes (24) up-regulated in a nontumor tissue in a laterecurrence group of type B hepatocellular carcinoma casesTable 2: Genes (10) up-regulated in a nontumor tissue in a laterecurrence group of type C hepatocellular carcinoma casesTable 3: Genes (137) up-regulated in a tumor tissue in a late recurrencegroup of type B hepatocellular carcinoma casesTable 4: Genes (104) up-regulated in a tumor tissue in a late recurrencegroup of type C hepatocellular carcinoma casesTable 5: Genes (48) up-regulated in a nontumor tissue in an earlyrecurrence group of type B hepatocellular carcinoma casesTable 6: Genes (12) up-regulated in a nontumor tissue in an earlyrecurrence group of type C hepatocellular carcinoma casesTable 7: Genes (75) up-regulated in a tumor tissue in an earlyrecurrence group of type B hepatocellular carcinoma casesTable 8: Genes (38) up-regulated in a tumor tissue in an earlyrecurrence group of type C hepatocellular carcinoma cases

TABLE 1 Genes (24) up-regulated in nontumor tissue in late recurrencegroup of hepatitis B cases (BNgood) No. Gene Overlapped group 1 TNFSF142 MMP2 3 SAA2 Late recurrence group (type B, tumor) 4 COL1A1 5 COL1A2 6DPYSL3 7 PPARD 8 LUM 9 MSTP032 10 CRP 11 TRIM38 12 S100A6 13 PZP 14 EMP115 AI590053 16 MAP3K5 17 TIMP1 18 GSTM1 Late recurrence Late recurrencegroup (type B, tumor) group (type C, tumor) 19 CSDA 20 GSTM2 Laterecurrence Late recurrence group (type B, tumor) group (type C, tumor)21 SGK Late recurrence group (type B, tumor) 22 LMNA 23 MGP 24 LTBP2

TABLE 2 Genes (10) up-regulated in nontumor tissue in late recurrencegroup of hepatitis C cases (CNgood) No. Gene Overlapped group 25 M10098Late recurrence Late recurrence group (type B, tumor) group (type C,tumor) 26 PSMB8 27 RALGDS 28 APOL3 29 GBP1 30 RPS14 31 CXCL9 32DKFZp564F212 33 CYP1B1 34 TNFSF10

TABLE 3 Genes (137) up-regulated in tumor tissue in late recurrencegroup of hepatitis B cases (BTgood) No. Gene Overlapped group 35 HP 25M10098 Late recurrence group (type C, tumor) Late recurrence group (typeC, nontumor) 36 CYP2E1 37 HDL Late recurrence group (type C, tumor) 38GPX4 39 G0S2 40 HAO2 41 ATF5 Late recurrence group (type C, tumor) 42MT1F Late recurrence group (type C, tumor) 43 CYP3A4 Late recurrencegroup (type C, tumor) 44 Scd 45 SERPINA7 46 AKR1D1 47 AL031602 48 TSC50118 GSTM1 Late recurrence group (type B, nontumor) Late recurrence group(type C, tumor) 3 SAA2 Late recurrence group (type B, nontumor) 49 BHMTLate recurrence group (type C, tumor) 50 HADHSC 51 FBXO9 52 KIAA0442 53KIAA0293 Late recurrence group (type C, tumor) 54 IGHG3 55 ADH2 Laterecurrence group (type C, tumor) 20 GSTM2 Late recurrence group (type B,nontumor) Late recurrence group (type C, tumor) 56 PPIF 57 ALDH8A1 58IGLJ3 59 HCN3 60 ADH6 Late recurrence group (type C, tumor) 61 AK02720Late recurrence group (type C, tumor) 62 NET-6 63 CYP2D6 64 MAFB 65 GHR66 KHK 67 ADFP 68 LCE 69 MPDZ Late recurrence group (type C, tumor) 70TEM6 71 KIAA0914 72 KLKB1 73 M11167 Late recurrence group (type C,tumor) 21 SGK Late recurrence group (type B, nontumor) 74 EHHADH 75 MBL2Late recurrence group (type C, tumor) 76 APP 77 MT1G 78 TPD52L1 Laterecurrence group (type C, tumor) 79 CXCL10 80 AI972416 81 FCGR2B 82 IGL@83 FLJ10134 84 PPAP2B 85 CDC42 86 HBA2 87 CYP1A2 Late recurrence group(type C, tumor) 88 CYP2B6 89 DKFZP586B1621 90 MTP 91 X07868 92 RNAHPLate recurrence group (type C, tumor) 93 HLF Late recurrence group (typeC, tumor) 94 PPP1R3C 95 CDC2L2 96 NRIP1 97 GPD1 98 KIAA1053 99 CCL19 100CRI1 101 THBS1 Late recurrence group (type C, tumor) 102 SLC5A3 103GADD45B 104 AGL 105 ADK 106 IGKC 107 CYP2A6 Late recurrence group (typeC, tumor) 108 GADD45A Late recurrence group (type C, tumor) 109 FLJ20701110 LOC57826 111 SLC2A2 112 CIRBP 113 CGI-26 114 DEFB1 115 HMGCS1 116ODC1 117 GLUL Early recurrence group (type B, nontumor) Late recurrencegroup (type C, tumor) 118 CYP27A1 119 SULT2A1 Late recurrence group(type C, tumor) 120 AK024828 121 PHLDA1 122 NR1I2 123 MSRA 124 RNASE4125 AI339732 126 HBA2 127 AL050025 128 CSAD 129 SID6-306 130 NM024561131 BCKDK 132 SLC6A1 133 CG018 134 GNE 135 CKLFSF6 136 COMT 137 AL135960138 KIAA0179 139 c-maf 140 OSBPL11 141 R06655 Late recurrence group(type C, tumor) 142 KIAA04461 143 IGF1 Late recurrence group (type C,tumor) 144 HBA1 145 LOC55908 146 ENPEP 147 TXNIP 148 KIAA0624 149 ENPP1150 CYP4F3 151 CAV2 152 BE908931 153 LECT2 154 MLLT2 155 FLR1 156 TF 157DAO 158 AI620911 159 GBP1 160 UGP2 161 GADD45B 162 SC4MOL 163 BE908931164 TUBB 165 EPHX2 166 SORD

TABLE 4 Genes (104) up-regulated in tumor tissue in late recurrencegroup of hepatitis C cases (CTgood) No. Gene Overlapped group 167 LEAP-1168 PPD 37 HDL Late recurrence group (type B, tumor) 43 CYP3A4 Laterecurrence group (type B, tumor) 107 CYP2A6 Late recurrence group (typeB, tumor) 25 M10098 Late recurrence Late recurrence group (type B,tumor) group (type C, nontumor) 169 RACE 170 SLC27A5 171 FLJ20581 172FLJ1851 53 KIAA0293 Late recurrence group (type B, tumor) 173 C9 174AL354872 175 AKR1C1 176 PCK1 18 GSTM1 Late recurrence group (type B,tumor) Late recurrence group (type B, nontumor) 87 CYP1A2 Laterecurrence group (type B, tumor) 177 ANGPTL4 178 AOX1 179 SDS 20 GSTM2Late recurrence group (type B, tumor) Late recurrence group (type B,nontumor) 73 M11167 Late recurrence group (type B, tumor) 180 CYP2C9 181SIPL 182 GLYAT 75 MBL2 Late recurrence group (type B, tumor) 183 CYP1A1184 CRP 141 R06655 Late recurrence group (type B, tumor) 185 ACADL 93HLF Late recurrence group (type B, tumor) 186 NR1I3 187 CA2 188 CYP2C8189 PON1 55 ADH2 Late recurrence group (type B, tumor) 92 RNAHP Laterecurrence group (type B, tumor) 190 AQP9 119 SULT2A1 Late recurrencegroup (type B, tumor) 191 SPP1 192 KIAA0934 193 AKAP12 194 APOF 195 FMO3196 SLC22A1 197 DCXR 198 CYP3A7 199 SOCS2 101 THBS1 Late recurrencegroup (type B, tumor) 41 ATF5 Late recurrence group (type B, tumor) 200BCRP 60 ADH6 Late recurrence group (type B, tumor) 201 humNRDR 202GADD45G 203 SRD5A1 204 ABCA8 61 AK026720 Late recurrence group (type B,tumor) 205 APOC4 206 FTHFD 207 ISG15 208 IGFBP2 49 BHMT Late recurrencegroup (type B, tumor) 209 DNASE1L3 210 SRD5A1 211 E2IG4 212 COL1A2 213C20orf46 214 ESR1 215 BLVRB 216 LRP16 217 SLC1A1 218 ABCB6 69 MPDZ Laterecurrence group (type B, tumor) 219 FBP1 220 ALAS1 221 IFIT1 222PPARGC1 223 Id-1H 224 RBP1 225 CSHMT 226 LOC155066 42 MT1F Laterecurrence group (type B, tumor) 227 AGXT2L1 228 TIMM17A 229 SEC14L2 230MAOA 231 MYC 232 ACAA2 233 AL109671 234 ABCA6 143 IGF1 Late recurrencegroup (type B, tumor) 235 GRHPR 236 HADH2 237 AFM 238 COL1A1 239 MTHFD1240 NMT2 108 GADD45A Late recurrence group (type B, tumor) 241 UGT2B15242 AR 78 TPD52L1 Late recurrence group (type B, tumor) 243 sMAP 117GLUL Early recurrence Late recurrence group (type B, tumor) group (typeB, nontumor) 244 dJ657E11.4

TABLE 5 Genes (48) up-regulated in nontumor tissue in early recurrencegroup of hepatitis B cases (BNbad) No. Gene Overlapped group 245 CTHEarly recurrence group (type B, tumor) 246 OAT 247 PRODH Earlyrecurrence group (type B, tumor) 248 CYP3A7 249 DDT Early recurrencegroup (type B, tumor) 250 PGRMC1 251 AKR1C1 252 HGD Early recurrencegroup (type B, tumor) 253 FHR-4 254 AL354872 255 FST Early recurrencegroup (type B, tumor) 256 COX4 257 APP 258 PSPHL 259 CYP1A1 260 ZNF216261 LEPR Early recurrence group (type B, tumor) 262 TOM1L1 263 PECR 264ALDH7A1 265 GNMT 266 OATP-C 267 AKR1B10 Early recurrence group (type C,nontumor) Early recurrence group (type B, tumor) 268 ANGPTL3 269 AASS270 CALR 271 BAAT 272 PMM1 273 RAB-R 117 GLUL Late recurrence group(type C, tumor) Late recurrence group (type B, tumor) 274 CSHMT 275UGT1A3 276 HSPG1 277 QPRT Early recurrence group (type C, nontumor) 278DEPP 279 CA2 Early recurrence group (type B, tumor) 280 FTHFD 281 LAMP1282 FKBP1A 283 BNIP3 284 MAP3K12 285 ASS Early recurrence group (type B,tumor) 286 ACTB 287 PLAB Early recurrence group (type B, tumor) 288ENO1L1 289 IGFBP3 290 UK114 291 ERF-1

TABLE 6 Genes (12) up-regulated in nontumor tissue in early recurrencegroup of hepatitis C cases (CNbad) No. Gene Overlapped group 292 ALB 293NR0B2 267 AKR1B10 Early recurrence Early recurrence group (type B,nontumor) group (type B, tumor) 294 MAFB 295 BF530535 296 MRPL24 297DSIPI 277 QPRT Early recurrence group (type B, nontumor) 298 VNN1 299IRS2 300 FMO5 301 DCN

TABLE 7 Genes (75) up-regulated in tumor tissue in early recurrencegroup of hepatitis B cases (BTbad) No. Gene Overlapped group 247 PRODHEarly recurrence group (type B, nontumor) 302 PLA2G2A Early recurrencegroup (type C, tumor) 303 SDS 304 LGALS3BP 305 BACE2 261 LEPR Earlyrecurrence group (type B. nontumor) 306 RCN1 307 MRC1 308 TM4SF5 309 NK4310 PABL 311 IGFBP2 312 GRINA 313 IF127 314 GP2 315 GA 316 P4HA2 317KYNU 318 PCK1 319 UQBP 320 HLA-DRB1 252 HGD Early recurrence group (typeB, nontumor) 321 HTATIP2 322 GGT1 323 CTSH 324 MVP 325 SLC22A1L 326 GMNN327 COM1 328 TM7SF2 245 CTH Early recurrence group (type B. nontumor)329 KDELR3 330 VPS28 279 CA2 Early recurrence group (type B. nontumor)331 SFN 332 NM023948 333 OPLAH 334 DGCR6 335 INSIG1 267 AKR1B10 Earlyrecurrence group (type B, nontumor) Early recurrence group (type C,nontumor) 336 PTGDS Early recurrence group (type C, tumor) 337 SLC25A15338 SEPW1 339 CD9 340 UQCRB 285 ASS Early recurrence group (type B,nontumor) 341 CPT1A 287 PLAB Early recurrence group (type B, nontumor)342 GPAA1 343 HF1 344 GPX2 345 COPEB 346 NDRG1 347 SYNGR2 348 GOT1 349POLR2K 350 AATF 255 FST Early recurrence group (type B, nontumor) 351OAZIN 352 RPL7 353 KIAA0128 354 CLDN7 355 ABCB6 356 GK 357 LU Earlyrecurrence group (type C, tumor) 358 TNFSF4 359 OSBPL9 360 GSN 361LGALS4 249 DDT Early recurrence group (type B, nontumor) 362 EIF3S3 363SLC12A2 364 RAMP1 365 HSPB1 366 AI201594

TABLE 8 Genes (38) up-regulated in tumor tissue in early recurrencegroup of hepatitis C cases (CTbad) No. Gene Overlapped group 367 BL34368 AL022324 369 IGHM 370 TXNIP 371 FSTL3 372 AW978896 373 NM018687 374L48784 375 AJ275355 376 PER1 377 CYBA 302 PLA2G2A Early recurrence group(type B, tumor) 378 SGK 379 FKBP11 380 AI912086 381 IGLJ3 382 IGKC 336PTGDS Early recurrence group (type B, tumor) 383 M20812 384 AGRN 385IL2RG 386 X07868 387 PKM2 388 FGFR3 389 TRB@ 390 TNFAIP3 391 TTC3 392LPA 393 AL049987 394 IER5 395 BSG 396 TM4SF3 397 HMGB2 357 LU Earlyrecurrence group (type B, tumor) 398 CCL19 399 PAM 400 PIK3R1 401RANGAP1

In Table 5, “CTH” and “AL354872” are genes, which encode the sameprotein.

The above-described genes can be included in a kit for evaluatingcancer, singly or in combination, as appropriate. Examples of a gene setconsisting of several genes may include those shown in Table 16(described later). The above genes may have the partial sequencethereof. Such genes can be used as probes for detecting the expressionof the genes shown in the table.

Moreover, the kit of the present invention may comprise primers used forgene amplification, a buffer solution, polymerase, etc.

With regard to such primers used for gene amplification, the DNAsequence and mRNA sequence of each gene sequence are obtained fromdatabase, and in particular, information including the presence orabsence of a variant and exon-intron structure is obtained. The samesequences as sequences of portions corresponding to coding regions areused as target. One primer is intended to bridge over an adjacent exon,and it is designed such that only mRNA is detected. Otherwise, primercandidates are obtained using the web software “Primer3” (provided bySteve Rozen and Whitehead Institute for Biomedical Research), andthereafter, homology search is carried out using BLAST (NCBI) search, soas to select primers, which are able to avoid miss-annealing to similarsequences.

The sequence numbers of preferred primers are represented by the generalformulas 2n−1 and 2n (wherein n represents an integer between 1 and114). In the present invention, a primer represented by 2n−1 and aprimer represented by 2n can be used as a set of primers. For example,when n is 1, a primer set consisting of the primers shown in SEQ ID NOS:1 and 2 can be used, and when n is 2, a primer set consisting of theprimers shown in SEQ ID NOS: 3 and 4 can be used. Particularly preferredprimers can be obtained, when n is 2, 4, 7, 9, or 17.

Moreover, in (1) above, it is also possible to carry out thequantitative analysis of gene expression via immuno-dot blot assay orimmunostaining. Such immuno-dot blot assay or immunostaining can becarried out according to common methods using an antibody reacting withthe expression products of the genes shown in Tables 1 to 8. As such anantibody, a commercially available antibody may be used, or an antibodyobtained by immunization of animals such as a mouse, a rat, or a rabbit,may also be used.

The present invention will be more specifically described in thefollowing examples. However, these examples are not intended to limitthe technical scope of the present invention.

EXAMPLE 1 Detection of Up-Regulated Gene in Hepatocellular CarcinomaCases

As described below, using human hepatic tissues obtained from type B andtype C hepatocellular carcinoma cases, molecules for suppressing therecurrence of hepatocellular carcinoma were identified at a gene level.

In order to understand a recurrence mechanism occurring after anoperation to resect hepatocellular carcinoma and determine a genecapable of predicting the presence or absence of recurrence, geneexpression profile analysis was carried out, using several cases, therecurrence periods of which were different. 51 cases, which were atstages I and II based on TNM classification, were used as targets. 5cases wherein the cancer had not recurred for 4 or more years after theoperation, and 5 cases wherein the cancer had recurred within 1 yearafter the operation, were selected. Thereafter, expression analysis wascarried out using an HG-U133A array manufactured by Affymetrix.

The TRIzol reagent (Life Technologies, Gaithersburg, Md.) was added tofrozen tissues, and the obtained mixture was then homogenated withPolytron. Thereafter, chloroform was added to the homogenate, and theywere then fully mixed, followed by centrifugation. After completion ofthe centrifugation, the supernatant was recovered, and an equivalentamount of isopropanol was added thereto. Thereafter, the precipitate oftotal RNA was recovered by centrifugation.

Type B hepatocellular carcinoma cases (wherein the causal virus is ahepatitis B virus) were divided into the following groups: the nontumortissues and tumor tissues of 2 early recurrence cases; and the nontumortissues and tumor tissues of 2 late recurrence cases. Also, type Chepatocellular carcinoma cases (wherein the causal virus is a hepatitisC virus) were divided into the following groups: the nontumor tissuesand tumor tissues of 3 early recurrence cases; and the nontumor tissuesand tumor tissues of 3 late recurrence cases. Thus, the total 8 groupswere subjected to expression analysis.

For each sample group, 15 μg of total RNA was prepared. Thereafter,biotin-labeled cRNA was synthesized based on GeneChip ExpressionAnalysis Technical Manual by Affymetrix. Using T7-(dt)₂₄ primer andSuperscript II reverse transcriptase (Invitrogen Life Technology), thereaction was carried out for 1 hour, so as to synthesize first strandcDNA. Thereafter, E. coli DNA ligase, E. coli DNA polymerase, and E.coli RNase H were added thereto, and the obtained mixture was thenallowed to react at 16° C. for 2 hours. Finally, T4 DNA polymerase wasadded to the reaction product, so as to synthesize double strand cDNA.After cleanup of the cDNA, the BioArray high yield RNA transcriptlabeling kit (Affymetrix, Inc, CA) was used for in vitro transcriptionat 37° C. for 4 hours, so as to synthesize biotin-labeled cRNA. Ahybridization probe solution was prepared based on the Technical Manual,and the above solution was then added to GeneChip HG-U133A (Affymetrix,Inc, CA; containing 22,283 human genes), obtained by pre-hybridizationat 45° C. for 45 minutes. Thereafter, hybridization was carried out at45° C. for 16 hours. Thereafter, the reaction product was washed withGeneChip Fluidics Station 400 (Affymetrix, Inc, CA), and was thenstained with streptavidin phycoerythrin and biotinylatedantistreptavidin. Thereafter, the resultant was subjected to scanningusing an HP GeneArray scanner (Affymetrix, Inc, CA).

The obtained data was analyzed using GeneSpring ver. 5.0(SiliconGenetics, Redwood, Calif.). After completion of normalization,using the signal of the control gene BioB used for intrinsicquantification as a detection limit (corresponding to several copies percell). A gene, which has a signal intensity of 100 or greater and alsohas a present flag in at least one chip, was defined as a target of theanalysis. As a result, 7,444 genes were determined to be such analysistargets. In nontumor tissues, genes having 2.5 times or more differencebetween the early recurrence group and the late recurrence group havebeen identified. In tumor tissues, genes having 3 times or moredifference between such two groups have been identified.

As a result, among the selected 7,444 genes, genes having 2.5 times ormore difference between the absence and the presence of recurrence innontumor tissues consisted of 34 up-regulated genes and 58down-regulated genes. On the other hand, genes having 3 time or moredifference between such two groups in tumor tissues consisted of 215up-regulated genes and 110 down-regulated genes. Among these genes, as agene up-regulated in the recurrence-absent group in both cases of type Band type C, no such genes were found in nontumor tissues, whereas 26genes were found in tumor tissues. On the other hand, among these genes,as a gene up-regulated in the recurrence-present group in both cases oftype B and type C, 2 genes were found in nontumor tissues, whereas 3genes were found in tumor tissues. Moreover, there were genesup-regulated in both tumor and nontumor tissue. There were found 5 genesup-regulated in the recurrence-absent group, and 10 genes up-regulatedin the recurrence-present group (Table 9).

It is to be noted that the total is not 402 but 401 in Table 9. This isbecause the overlapping of GLUL is a particular case.

TABLE 9 Genes associated with recurrence of hepatocellular carcinomaUp-regulated Up-regulated in late recurrence in early recurrence groupgroup nontumor tumor nontumor tumor tissue tissue tissue tissue Bothcases Hepatitis B 24 137 4 48 75 10 Hepatitis C 10 104 1 12 38 0 Bothtypes 0 26 2 3 Total 34 215 244 58 110 158 Total 401

From the results shown in Table 9, it can be said that with regard to adifference in recurrence prognosis, a change in gene expression isgreater in a tumor-tissue than in a nontumor tissue, and that such achange in gene expression is greater in type B hepatocellular carcinomacases than in type C hepatocellular carcinoma cases. In addition, thereare genes associated with recurrence prognosis, which are foundindependently of a causal virus, but unexpectedly, such genes are rare.As in the case of the development of cancer, it is considered thatdifferent mechanisms are involved in the recurrence of cancer, dependingon the type of a causal virus.

In the analysis of a sample phylogenetic tree, the expression profilesof all genes are first divided into nontumor tissues and tumor tissues.In each of such nontumor tissues and tumor tissues, a geneticaffiliation, which is not caused by recurrence prognosis but caused by acausal virus, was observed (FIG. 1). In FIG. 1, with regard to notationindicating each test group, such as “BNbad” or “BNgood,” the firstalphabet indicates the type of a virus. That is, “B” representshepatitis B virus, and “C” represents hepatitis C virus. The secondalphabet “N” represents a nontumor tissue, and “T” represents a tumortissue. Moreover, “bad” represents early recurrence, and “good”represents late recurrence.

It is considered that gene expression affecting recurrence prognosis iscaused by a change in the gene expression of limited genes.

As stated above, candidate genes capable of clarifying a recurrencemechanism or predicting the presence or absence of recurrence were found(Tables 1 to 8).

EXAMPLE 2 Study of Correlation Between the Recurrence Period and anExpression Level of Genes in Each Group in Type C HepatocellularCarcinoma Cases

As mentioned below, with regard to genes up-regulated in the nontumortissues of a late recurrence group and an early recurrence group in typeC hepatocellular carcinoma cases, the correlation between the recurrenceperiod and an expression level was studied.

The total 22 nontumor tissue samples, including 6 cases of type Chepatocellular carcinoma used in the gene expression profile analysis,were used as targets. The clinicopathological findings of each case andthe recurrence period (that is, the period of time in which the cancerhas not yet recurred) are shown in Table 10A.

TABLE 10A Type C hepatocellular carcinoma cases Nontumor Number ofmonths Case No. Sex Age tissue stage without recurrence Microarray 59 M66 CH I 84 Late recurrence group 18 M 68 LC I 58 Late recurrence group 6M 65 CH II 51 Late recurrence group 25 M 51 CH I 45 29 M 70 CH II 43 12M 66 CH II 41 4 M 65 CH I 40 48 F 65 LC I 39 31 M 60 LC I or II 38 16 M70 CH I 37 22 M 65 CH I 34 23 F 71 LC I 29 65 M 60 LC I 29 30 F 62 LC II28 10 M 56 LC I 26 23 M 62 CH II 16 26 M 70 LC I 16 14 M 62 CH II 14Early recurrence group 62 M 66 LC I 13 17 M 54 LC I 12 15 F 68 LC II 8Early recurrence group 44 M 58 CH I 4 Early recurrence group CH: chronichepatitis; LC: liver cirrhosis Stage of case 31: undetermined The term“number of months without recurrence” includes not only the number ofmonths required for recurrence, but also includes the investigationperiod in which recurrence was not observed.

In addition, the cases shown in Table 10A were changed or revised as aresult of follow-up study. Moreover, with regard to the total 35 cases,including cases added as the targets of the present example, theclinicopathological findings of each case and the recurrence period(that is, the period of time in which the cancer has not yet recurred)are shown in Table 10B.

TABLE 10B Type C hepatocellular carcinoma cases Nontumor Number ofmonths Case No. Sex Age tissue stage without recurrence Microarray 59 M66 CH I >94 Late recurrence group 6 M 65 CH II 65 Late recurrence group25 M 51 CH I >58 18 M 68 LC I 58 Late recurrence group 12 M 66 CH II 414 M 65 CH I >40 29 M 70 CH II 39 16 M 70 CH I >37 48 F 65 LC I 37 31 M60 LC I 37 80 M 73 CH II 34 22 M 65 CH I 33 3 F 71 LC I 29 65 M 60 LC I28 30 F 62 LC II 26 10 M 56 LC I 25 70 M 57 LC II 24 79 M 73 LC I 22 73M 50 CH II 20 81 F 69 LC I 17 26 M 70 LC I 16 72 M 71 LC II 16 69 M 66LC II 15 14 M 62 CH II 14 Early recurrence group 78 F 66 CH I 13 82 M 71CH I 13 17 M 54 LC I 12 71 M 57 LC II 12 77 F 65 LC I 10 62 M 66 LC I 974 M 67 CH II 9 15 F 68 LC II 8 Early recurrence group 76 M 72 NL I 7 75M 65 CH II 6 44 M 58 CH I 4 Early recurrence group CH: chronichepatitis; LC: liver cirrhosis; NL: normal liver The term “number ofmonths without recurrence” includes not only the number of monthsrequired for recurrence, but also includes the period in whichrecurrence has not yet been observed at the time of investigation.

With regard to the total 21 genes consisting of 9 genes (CNgood)up-regulated in the nontumor tissues of the late recurrence group shownin Table 2 and 12 genes (CNbad) up-regulated in the nontumor tissues ofthe early recurrence group shown in Table 6, the relationship betweenthe recurrence period and an expression level was analyzed.

First, total RNA was extracted from the nontumor liver tissue of eachcase by the same method as that described in Example 1 above.

In order to eliminate the influence of DNA mixed therein, the total RNAwas treated with DNase I (DNase I, TAKARA SHUZO, Kyoto, Japan) at 37° C.for 20 minutes, and it was then purified again with a TRIzol reagent.Using 10 μg of the total RNA, a reverse transcription reaction wascarried out with 100 μl of a reaction solution comprising 25 units ofAMV reverse transcriptase XL (TAKARA) and 250 μmol of a 9-mer randomprimer.

Real-time PCR was carried out using 0.25 to 50 ng each of syntheticcDNA. 25 μl of a reaction solution, SYBR Green PCR Master mix (AppliedBiosystems, Foster City, Calif.) was used, and ABI PRISM 7000 (AppliedBiosystems) was employed. PCR was carried out under conditions whereinpreliminary heating was carried out at 95° C. for 10 minutes, andthereafter, a cycle consisting of 95° C. for 15 seconds and 60° C. (or65° C.) for 60 seconds, was repeated 40 to 45 times.

Using glyceraldehyde 3-phosphatase dehydrogenase (GAPDH) or 18S rRNA asan internal standard gene of each sample, relative quantitativeanalysis, and partially, absolute quantitative analysis, were carriedout. Values obtained by subjecting standard samples to serial dilutionand simultaneous measurement, were used to produce a calibration curve.A threshold line for optimization of such a calibration curve wasdetermined, and the number of threshold PCR cycles, a threshold cyclevalue (Ct) was then obtained for each sample. A Δ Ct value was obtainedby subtracting the Ct value of GAPDH or 18S rRNA from the Ct value of atarget gene, and the obtained value was defined as the relativeexpression level of the target gene. Moreover, values obtained using theformula (2(^(−ΔCt))) were used for evaluation of a linear expressionlevel.

On the other hand, with regard to genes whose absolute expression levelcan be calculated relative to a calibration curve, the absoluteexpression level of a target gene and that of an internal standard genewere obtained. Thereafter, the ratio of the target gene expressionlevel/the internal standard gene expression level was calculated foreach sample, and it was used for evaluation. All such measurements werecarried out in a duplicate manner.

In Tables 11A, 11B, 12A, and 12B, the term “correspondence withmicroarray” is used to mean that when the ratio between the laterecurrence group (case Nos. 59, 18, and 6) and the early recurrencegroup (case Nos. 14, 15, and 44) was obtained from the results ofquantitative PCR performed on 6 cases (case Nos. 59, 18, 6, 14, 15, and44 in Table 10A or 10B) used in the microarray analysis, genes, theabove ratio of which was 1.5 or greater, corresponded with the resultsof the microarray in Example 1. Genes corresponding with the microarrayresults were indicated with the mark O. The above ratio is 1.5 orgreater, and preferably 2 or greater. The number in the parenthesisadjacent to the mark O indicates such a ratio (the average ratio of 3cases). The mark X in the “correspondence with microarray” columnindicates a gene that does not correspond with the microarray results.The mark XX indicates a gene, which exhibits an opposite correlationwith the microarray results.

In Tables 11A, 11B, 12A, and 12B, the term “correlation” is used to meana correlation between the gene expression level and the recurrenceperiod in 22 cases, or in 31 cases wherein the number of months in whichthe recurrence of the cancer had occurred was determined. In the case ofa significant correlation, O or the r value was indicated, and further,the p value was also indicated.

In Tables 11B and 12B, with regard to genes exhibiting a significantdifference in expression levels between 19 cases of the recurrencewithin 24 months, and 6 cases of no recurrence for 40 months or more(the upper case of the “significant difference between two groups”column in Tables 11B and 12B) or 4 cases of no recurrence for 58 monthsor more (the lower case of the “significant difference between twogroups” column in Tables 11B and 12B), p values (Mann-Whitney U test)were shown in the “significant difference between two groups” column.

Primer sequences (sense strand (forward), antisense strand (reverse))used for the test are shown in Tables 11A, 11B, 12A, and 12B (SEQ IDNOS: 1 to 88).

The results obtained by analyzing the 9 gene candidates (CNgood)up-regulated in nontumor tissues in the late recurrence group of type Chepatocellular carcinoma cases are shown in Tables 11A and 11B. Table11A shows the analysis results obtained by quantitative PCR, which wasperformed on the cases shown in Table 10A as targets, under theconditions shown in Table 11A using GAPDH as an internal standard gene.

TABLE 11AResults of quantitative POR of “genes up-regulated in nontumor tissues in laterecurrence group of hepatitis C cases” SEQ  Correspondence Forward/Primer sequence  ID Annealing with  No. Gene reverse (5′-3′)  NO.temperature microarray Correlation 26 PSMB8 F AGACTGTCAGTACTGGGAGC 1 60°C. ◯(2.52) R GTCCAGGACCCTTCTTATCC 2 27  RALGDS F GACGTGGGAAGACGTTTCCA 360° C. ◯(4.13) ◯(p = 0.0118) R TGGATGATGCCCGTCTCCTT 4 28 APOL3 FAATTGCCCAGGGATGAGGCA 5 60° C. ◯(2.69) R TGGACTCCTGGATCTTCCTC 6 29 GBP1 FGAGAACTCAGCTGCAGTGCA 7 65° C. ◯(6.00) ◯(p = 0.0031) RTTCTAGCTGGGCCGCTAACT 8 30 RPS14 F GACGTGCAGAAATGGCACCT  9 60° C. X(0.96)R CAGTCACACGGCAGATGGTT 10 31 CXCL9 F CCTGCATCAGCACCAACCAA 11 65° C. ◯(11.5) R TGGCTGACCTGTTTCTCCCA 12 32 DKFZp564F212 F CCACATCCACCACTAGACAC13 60° C. ◯(4.75) ◯(p = 0.0541) R TGACAGATGTCCTCTGAGGC 14 33 CYP1B1 FCCTCTTCACCAGGTATCCTG 15 60° C. ◯(2.33) R CCACAGTGTCCTTGGGAATG 16 34TNFSF10 F GCTGAAGCAGATGCAGGACA 17 60° C. ◯(2.50) ◯(p = 0.0424) RCTAACGAGCTGACGGAGTTG 18 With regard to “correspondence with microarray,”the ratio of late recurrence group and early recurrence group wasobtained from the results of quantitative PCR performed on 6 cases usedin microarray analysis, and genes with the ratio of 1.5 or greater wereindicated with ◯. With regard to “correlation”, genes exhibitingcorrelation between the gene expression levels of 22 cases and theperiod of time required for recurrence were indicated with ◯, and the pvalues thereof were also shown.

As a result, it was found that 8 genes corresponded with the microarrayresults, and that among such genes, 4 genes (RALGDS, GBP1, DKFZp564F212,and TNFSF10) exhibited a correlation with the recurrence period.

Likewise, Table 11B shows the analysis results obtained by quantitativePCR, which was performed on the 10 genes shown in Table 11B and thecases shown in Table 10B as targets, under the conditions shown in thetable using GAPDH or 18S rRNA as an internal standard gene.

TABLE 11BResults of quantitative PCR of “genes up-regulated in nontumor tissues in late recurrence group of hepatitis C cases”  Significant Significant   Correspondence Correspondence differencedifference with microarray, with microarray, between between Forward/Primer sequence SEQ  Annealing normalized with normalized withCorrelation Correlation two groups two groups No. Gene reverse (5′-3′)ID NO. temperature GAPDH 18S rRNA (GAPDH) (18S rRNA) (GAPDH) (18S rRNA)1 M10098 F GGAGGTTCGAAGACGATCAG 19 65° C. X X (0.60) — RGTGGTGCCCTTCCGTCAATT 20 2 PSMB8 F AGACTGTCAGTACTGGGAGC 21 60° C. ◯(1.92)◯(3.60) r = 0.421 R GTCCAGGACCCTTCTTATCC 22 (p = 0.0177) 3 RALGDS FGTGTGGCCAACTGTGTCATC 23 65° C. ◯(6.71) ◯(8.23) r = 0.377 RCTTCAGACGGTGGATGGAGT 24 (p = 0.0361) 0.0314 4 APOL3 FAATTGCCCAGGGATGAGGCA 25 60° C. ◯(1.65) ◯(2.13) R TGGACTCCTGGATCTTCCTC 265 GBP1 F AACAAGCTGGCTGGAAAGAA 27 65° C. ◯(6.87) ◯(5.76) r = 0.359 r =0.374 R GTACACGAAGGTGCTGCTCA 28 (p = 0.0469) (p = 0.0377) 6 RPS14 FGACGTGCAGAAATGGCACCT 29 60° C. ◯(2.02) ◯(3.35) r = 0.383 r = 0.4580.0357 R CAGTCACACGGCAGATGGTT 30 (p = 0.0329) (p = 0.0089) 7 CXCL9 FCCTGCATCAGCACCAACCAA 31 65° C. ◯(14.3) ◯(12.5) r = 0.392 r = 0.4370.0131 R TGGCTGACCTGTTTCTCCCA 32 (p = 0.0282) (p = 0.0132) 8DKFZp564F212 F TGGGCAAGTGAGGTCTTCTT 33 60° C. ◯(4.69) ◯(8.40) r = 0.5010.0485 0.0075 R CTGAGGATCACTGGTATCGC 34 (p = 0.0036) 0.0094 0.0074 9CYP1B1 F GACCCCCAGTCTCAATCTCA 35 65° C. ◯(4.29) ◯(4.78) r = 0.424 r =0.553 0.0417 0.0042 R AGTCTCTTGGCGTCGTCAGT 36 (p = 0.0167) (p = 0.001)0.0045 0.0094 10 TNFSF10 F GCTGAAGCAGATGCAGGACA 37 60° C. ◯(3.71)◯(4.54) r = 0.460 r = 0.603 0.0062 R CTAACGAGCTGACGGAGTTG 38 (p =0.0085) (p = 0.0002) 0.0426 GAPDH F GGTCGGAGTCAACGGATTTG 39 60° C. RGGATCTCGCTCCTGGAAGAT 40 The expression level of each gene was evaluatedby quantitative PCR using GAPDH as a control gene and was eXpressed as arelative value to the expression level of the control gene. With regardto “correspondence with microarray,” the ratio of the late recurrencegroup and the early recurrence group was obtained from the results ofquantitative PCR on 6 cases used for microarray analysis, and genes withthe ratio of 1.5 or greater were indicated with ◯. With regard to“correlation,” genes exhibiting a correlation between the geneexpression levels of 31 cases wherein the number of months of recurrencehad been determined, and the period required for recurrence, wereindicated with the r value and the p value. In “significant differencebetween two groups,” with regard to genes exhibiting a significantdifference in expression levels between 19 cases of the recurrencewithin 24 months, and 6 cases of no recurrence for 40 months or more(the upper case) or 4 cases of no recurrence for 56 months or more (thelower case), p values were indicated (Mann-Wnitney U test).

As a result, it was found that when GAPDH was used as an internalstandard gene, all the 9 gene candidates exhibiting up-regulation in thelate recurrence group corresponded with the microarray results, and thatamong such genes, 5 genes exhibited a correlation with the recurrenceperiod. In addition, when 18S rRNA was used as an internal standard genealso, all the above 9 gene candidates corresponded with the microarrayresults, and among them, 8 genes exhibited a correlation with therecurrence period.

A significant difference test was carried out on two groups, the laterecurrence group and the early recurrence group. As a result, it wasfound that when GAPDH was used as a standard gene, 3 genes exhibited asignificant difference, and that when 18S rRNA was used as a standardgene, 5 genes exhibited a significant difference.

Subsequently, the results obtained by analyzing the 12 gene candidates(CNbad) up-regulated in nontumor tissues in the early recurrence groupof type C hepatocellular carcinoma cases are shown in Tables 12A and12B. Table 12A shows the analysis results obtained by quantitative PCR,which was performed on the cases shown in Table 10A as targets, underthe conditions shown in Table 12A using GAPDH as an internal standardgene.

TABLE 12A Results of quantitative PCR of “genes up-regulated in nontumor tissues in early recurrence group of hepatitis C cases” SEQ  AnnealingCorrespondence  No. Gene F/R Primer sequence (5′-3′) ID NO. temperaturewith microarray Correlation 292 ALB F CAAAGCATGGGCAGTAGCTC 41 60° C.◯(2.19) R CAAGCAGATCTCCATGGCAG 42 293 NR0B2 F TCTTCAACCCCGATGTGCCA 4360° C. ◯(1.48) R AGGCTGGTCGGAATGGACTT 44 267 AKR1B10 FCTTGGAAGTCTCCTCTTGGC 45 60° C. ◯(2.44) R ATGAACAGGTCCTCCCGCTT 46 294MAFB F ACCATCATCACCAAGCGTCG 47 60° C. ◯(1.56) R TCACCTCGTCCTTGGTGAAG 48295 BF530535 F GTCGCCTCACCATCTGTACA 49 65° C. ◯(3.74) RCTGGAGGACAGCTGCCAATA 50 296 MRPL24 F TCCTAGAAGGCAAGGATGCC 51 60° C. X(0.92) R GTGGGTTTCCTGTCCATAGG 52 297 DSIPI F AACAGGCCATGGATCTGGTG 5365° C. ◯(1.85) R AGGACTGGAACTTCTCCAGC 54 279 QPRT F AGGATAACCATGTGGTGGCC55 60° C. X X(0.413) ◯(p = 0.0092) R TGCAGCTCCTCTGGCTTGAA 56 298 VNN1 FGCTGGAACTTCAACAGGGAC 57 60° C. X(1.11) R CTGAGGATCACTGGTATCGC 58 299IRS2 F TGAAGCTCAACTGCGAGCAG 59 60° C. ◯(1.57) R ACGATTGGCTCTTACTGCGC 60300 FMO5 F ACACAGAGCTCTGAGTCAGC 61 60° C. X(1.13) R TCCAGGTTAGGAGGGAAGAC62 301 DCN F CCTCAAGGTCTTCCTCCTTC  63 60° C. X(0.74) RCACCAGGTACTCTGGTAAGC 64 QPRT gene is a gene exhibiting an oppositecorrelation.

As a result, 7 genes corresponded with the microarray results. No genessignificantly exhibited a correlation with the recurrence period.However, the QPRT gene significantly exhibited an opposite correlation.Accordingly, this gene was identified as a gene up-regulated in nontumortissues in the late recurrence group.

Likewise, Table 12B shows the analysis results obtained by quantitativePCR, which was performed on the cases shown in Table 10B as targets,under the conditions shown in Table 12B using GAPDH or 18S rRNA as aninternal standard gene.

TABLE 12B Results of quantitative PCR of “genes up-regulated in nontumor tissues in early recurrence group of hepatitis C cases”  Significant Significant   Correspondence  Correspondence differencedifference SEQ with microarray, with microarray, between betweenForward/ ID  Annealing normalized with normalized with  CorrelationCorrelation  two groups  two groups No. Gene reversePrimer sequence (5′-3′)   NO. temperature  GAPDH 18S rRNA (GAPDH)(18S rRNA) (GAPDH) (18S rRNA) 1 ALB F CAAAGCATGGGCAGTAGCTC 65 60° C.X(1.25) X X(0.64) R CAAGCAGATCTCCATGGCAG 66 2  NR0B2 FTCTTCAACCCCGATGTGCCA 67 65° C. X(1.13) X(1.04) 0.0220 RAGGCTGGTCGGAATGGACTT 68 3 AKRlB10 F CTTGGAAGTCTCCTCTTGGC 69 60° C.X(0.83) X(0.92) R ATGAACAGGTCCTCCCGCTT 70 4 MAFB F GACGTGAAGAAGGAGCCACT71 60° C. X(0.71) X X(0.61) r = 0.422 r = 0.501 0.0281 RCGCCATCCAGTACAGATCCT 72 (p = (p = 0.0171) 0.0036) 5 BF530535 FTGCCATAGTGGCTTGATTTG 73 60° C. ◯(0.82) X X (0.48) 0.0486 RTCAGAATCCCCATCATCACA 74 6 MRPL24 F CAGGGCAAAGTGGTTCAAGT 75 65° C.X X(0.46) X X(0.31) r = 0.431 r = 0.483 0.0083 0.0083 0.0426 RTCTCAGTGGGTTTCCTGTCC 76 (p = (p = 0.0040 0.0147) 0.0053) 7 DSIPI FAACAGGCCATGGATCTGGTG 77 65° C. ◯(2.57) ◯(1.75) R AGGACTGGAACTTCTCCAGC 788 QPRT F AACTACGCAGCCTTGGTCAG 79 65° C. X(0.72) X X(0.54) 0.0075 0.0231R TGGCAGTTGAGTTGGGTAAA 80 9 VNN1 F GCTGGAACTTCAACAGGGAC 81 65° C.X X(0.65) X X(0.41) 0.0018 0.0009 0.0074 R CTGAGGATCACTGGTATCGC 820.0035 10 IRS2 F CCACTCGGACAGCTTCTTCT 83 65° C. X(0.78) X X(0.63) r =0.419 r = 0.462 R GGATGGTCTCGTGGATGTTC 84 (p = (p = 0.0181) 0.0082) 11FMO5 F ACACAGAGCTCTGAGTCAGC 85 60° C. X(1.02) X X(0.62) RTCCAGGTTAGGAGGGAAGAC 86 12 DCN F CCTCAAGGTCTTCCTCCTTC 87 60° C. X(1.40)X(0.77) R CACCAGGTACTCTGGTAAGC 88 With regard to “correspondence withmicroarray,” the ratio of the late recurrence group and the earlyrecurrence group was obtained from the results of quantitative PCR on 6cases used for microarray analysis, and genes with the ratio of 1.5 orgreater were indicated with ◯. X indicates no difference, and X Xindicates an opposite correlation. With regard to “correlation,” genesexhibiting a correlation between the gene expression levels of 31 caseswherein the number of months of recurrence had been determined, and theperiod required for recurrence, were indicated with the r value(opposite correlation) and the p value. With regard to “significantdifference between two groups,” genes exhibiting a significantdifference in expression levels between 19 cases of the recurrencewithin 24 months, and 6 cases of no recurrence for 40 months or more(the upper case) or 4 cases of no recurrence for 58 months or more (thelower case). p values (Mann-Whitney U test) were indicated.

As a result, it was found that when GAPDH or 18S rRNA was used as aninternal standard gene, among 12 gene candidates exhibitingup-regulation in the early recurrence group, 1 gene corresponded withthe microarray results. However, when GAPDH was used as an internalstandard gene, the MAFB gene, the MRPL24 gene, the VNN1 gene, and IRS2gene significantly exhibited an opposite correlation. In addition, when18S rRNA was used as an internal standard gene, the NROB2 gene, the MAFBgene, the BF530535 gene, the MRPL24 gene, the QPRT gene, the VNN1 gene,and the IRS2 gene significantly exhibited an opposite correlation.Accordingly, these genes were identified as genes up-regulated innontumor tissues in the late recurrence group.

As stated above, as a result of the studies carried out under variousconditions, the following 15 genes were identified as genes expressed innontumor tissues, which can be used for prediction of the recurrence ofcancer in type C hepatocellular carcinoma cases: the PSMB8 gene, theRALGDS gene, the GBP1 gene, the RPS14 gene, the CXCL9 gene, theDKFZp564F212 gene, the CYP1B1 gene, the TNFSF10 gene, the NROB2 gene,the MAFB gene, the BF530535 gene, the MRPL24 gene, the QPRT gene, theVNN1 gene, and the IRS2 gene. The meanings of the aforementioned genesare as follows:

PSMB8 gene (which is also referred to as LMP7 gene): A proteasomesubunit, beta type, 8 geneRALGDS gene: A ral guanine nucleotide dissociation stimulator geneGBP1 gene: A guanylate-binding protein 1 geneRPS14 gene: A ribosomal protein S14 geneCXCL9 gene: A chemokine (C-X-C motif) ligand 9 geneDKFZp564F212 gene: An expression gene discovered by German Human GenomeProject, whose gene product has not been identified and whose functionshave not yet been predicted.CYP1B1 gene: A cytochrome P450, family 1, subfamily B, polypeptide 1geneTNFSF10: An abbreviation of TNF (ligand) super family, member 10, and aTNF-related apoptosis inducing ligand (TRAIL) geneNR0B2 gene: A nuclear receptor subfamily 0, group B, member 2 geneMAFB gene: A v-maf musculoaponeurotic fibrosarcoma oncogene homolog BgeneBF530535 gene: A gene whose gene product has not been identified andwhose functions have not yet been predicted.MRPL24 gene: A mitochondrial ribosomal protein L24 geneQPRT gene: A quinolinate phosphoribosyltransferase geneVNN1 gene: A vanin 1 geneIRS2 gene: An insulin receptor substrate 2 gene

EXAMPLE 3 Study of Correlation Between the Recurrence Period and anExpression Level of Genes in Each Group in Type B HepatocellularCarcinoma Cases

As mentioned below, with regard to genes up-regulated in the nontumortissues of a late recurrence group and an early recurrence group in typeB hepatocellular carcinoma cases, the correlation between the recurrenceperiod and an expression level was studied.

The total 16 nontumor tissue samples, including 4 cases of type Bhepatocellular carcinoma used in the gene expression profile analysis,were used as targets. The clinicopathological findings of each case andthe recurrence period (that is, the period of time in which the cancerhas not yet recurred) are shown in Table 13.

TABLE 13 Type B hepatocellular carcinoma cases Number of months Case No.Sex Age Nontumor tissue stage without recurrence Microarray 67 M 45 CHII >99 Late recurrence group 87 M 45 CH I >92 85 F 64 NL II 84 93 M 58CH I >67 94 F 59 LC I >66 60 M 60 NL I 64 Late recurrence group 35 M 69CH I >48 45 M 68 CH I >48 84 M 51 CH I/II 47 54 (86) M 52 CH II 27 47 M36 CH I 23  8 M 68 CH II 17 13 F 51 CH I 14 Early recurrence group 42(88) M 74 CH II 14 89 M 45 CH II 9  9 M 44 CH II 7 Early recurrencegroup CH: chronic hepatitis; LC: liver cirrhosis; NL; normal liver Theterm “stage I/II” indicates that it is unknown whether the stage isstage I or II. The term “number of months without recurrence” includesnot only the number of months required for recurrence, but also includesthe investigation period in which recurrence was not observed.

With regard to the total 71 genes consisting of 24 genes (BNgood)up-regulated in the nontumor tissues of the late recurrence group shownin Table 1 and 47 genes (BNbad) up-regulated in the nontumor tissues ofthe early recurrence group shown in Table 5, the relationship betweenthe recurrence period and an expression level was analyzed.

First, total RNA was extracted from the nontumor hepatic tissue of eachcase by the same method as that described in Example 1 above.

In order to eliminate the influence of DNA mixed therein, the total RNAwas treated with DNase I (DNase I, TAKARA SHUZO, Kyoto, Japan) at 37° C.for 20 minutes, and it was then purified again with a TRIzol reagent.Using 10 μg of the total RNA, a reverse transcription reaction wascarried out with 100 μl of a reaction solution comprising 25 units ofAMV reverse transcriptase XL (TAKARA) and 250 pmol of a 9-mer randomprimer.

Real-time PCR was carried out using 0.25 to 50 ng each of syntheticcDNA. 25 μl of a reaction solution, SYBR Green PCR Master mix (AppliedBiosystems, Foster City, Calif.) was used, and ABI PRISM 7000 (AppliedBiosystems) was employed. PCR was carried out under conditions whereinpreliminary heating was carried out at 95° C. for 10 minutes, andthereafter, a cycle consisting of 95° C. for 15 seconds and 60° C. (or65° C.) for 60 seconds, was repeated 40 to 45 times.

Using GAPDH or 18S rRNA as an internal standard gene of each sample,absolute quantitative analysis was carried out. Values obtained bysubjecting standard samples to serial dilution and simultaneousmeasurement, were used to produce a calibration curve.

The absolute expression level of a target gene and that of an internalstandard gene were obtained. Thereafter, the ratio of the target geneexpression level/the internal standard gene expression level wascalculated for each sample, and it was used for evaluation. All suchmeasurements were carried out in a duplicate manner.

As with the descriptions in Example 2, the term “correspondence withmicroarray” shown in Tables 14 and 15 is used to mean that when theratio of the late recurrence group (case Nos. 67 and 60) and the earlyrecurrence group (case Nos. 13 and 9) was obtained from the results ofquantitative PCR performed on 4 cases (case Nos. 67, 60, 13, and 9 inTable 13) used in the microarray analysis, genes, the above ratio ofwhich was 1.5 or greater, corresponded with the results of themicroarray in Example 1. The mark O is given to genes, when the aboveratio of is 1.5 or greater, and preferably 2 or greater. The number inthe parenthesis adjacent to the mark O indicates the value of such aratio. The mark X in the “correspondence with microarray” columnindicates a gene that does not correspond with the microarray results.The mark XX indicates a gene that exhibits an opposite correlation tothe microarray results.

In the “correlation” columns in Tables 14 and 15, with regard to genes,which exhibited a correlation between the gene expression level and therecurrence period in 10 cases wherein the number of months in which therecurrence of the cancer had occurred was determined, the r value andthe p value were described.

In the “significant difference between two groups” column in Tables 14and 15, with regard to genes exhibiting a significant difference inexpression levels between 6 cases of the recurrence within 24 months,and 8 cases of no recurrence for 48 months or more (the upper case ofthe “significant difference between two groups” in Tables 14 and 15) or6 cases of no recurrence for 60 months or more (the lower case of the“significant difference between two groups” in Tables 14 and 15), pvalues (Mann-Whitney U test) were indicated.

Primer sequences (sense strand (forward), antisense strand (reverse))used for the test are shown in Tables 14 and 15 (SEQ ID NOS: 89 to 228).

The results obtained by analyzing the 24 gene candidates (BNgood)up-regulated in nontumor tissues in the late recurrence group of type Bhepatocellular carcinoma cases are shown in Tables 14. Table 14 showsthe analysis results obtained by quantitative PCR, which was performedon the cases shown in Table 13 as targets, under the conditions shown inTable 14 using GAPDH or 18S rRNA as an internal standard gene.

TABLE 14Results of quantitative PCR of “genes up-regulated in nontumor tissues in late recurrence group of hepatitis B cases”Significant Significant Correspondence Correspondence  differencedifference with microarray, with microarray, between between Forward/Prime SEQ Annealing normalized with normalized with CorrelationCorrelation two groups two groups No. Gene reverse sequence (5′-3′) ID NO. temperature GAPDH 18S rRNA (GAPDH) (18S rRNA) (GADPH) (18S rRNA)1 TNFSF14 F CTGTTGGTCAGCCAGCAGT 89 65° C. ◯(6.11) ◯(2.36) RGAAAGCCCCGAAGTAAGACC 90 0.0065 2 MMP2 F CAAGGACCGGTTCATTTGGC 91 60° C.◯(3.82) ◯(2.09) R GAACACAGCCTTCTCCTCCT 92 3 SAA2 F TGCTCGGGGGAACTATGATG93 60° C. ◯(5.20) ◯(2.47) R GGCCTGTGAGTCTCTGGATA 94 4 COL1A1 FGGAAGAGTGGAGAGTACTGG 95 60° C. ◯(2.56) X(1.33) R ATCCATCGGTCATGCTCTCG 965 COL1A2 F GTATTCCTGGCCCTGTTGGT 97 60° C. ◯(2.92) ◯(1.52) RCTCACCCTTGTTACCGCTCT 98 6 DPYSL3 F CTTTGAAGGGATGGAGCTGC 99 65° C.◯(1.52) ◯(0.78) R ATCGTACATGCCCCTTGGGA 100 7 PPARD FGGCCTCTATCGTCAACAAGG 101 60° C. ◯(1.04) X X(0.40) R GCGTTGAACTTGACAGCAAA102 8 LUM F TACCAATGGTGCCTCCTGGA 103 60° C. ◯(1.39) ◯(0.82) RCCACAGACTCTGTCAGGTTG 104 9 MSTP032(RGS5) F CTGGAAAGGGCCAAGGAGAT 105 60°C. ◯(1.79) X(1.03) R TCTGGGTCTTGGCTGGTTTC 106 10 CRP FTGGCCAGACAGACATGTCGA 107 60° C. ◯(3.43) ◯(1.60) R TCGAGGACAGTTCCGTGTAG109 11 TRIM38 F TCTCTGGAGGCTGGAGAAAG 109 65° C. X(1.18) X X(0.49) RGTTTCCAGCTTCACAGCCCA 110 12 S100A6 F ATTGGCTCGAAGCTGCAGGA 111 60° C.◯(1.83) ◯(0.87) R GGAAGGTGACATACTCCTGG 112 13 PZP F TACTCCAATGCAACCACCAA113 65° C. ◯(4.39) ◯(2.15) r = 0.717 R AACACAAGTTGGGATGCACA 114 (p =0.0171) 14 EMP1 F TGGTGTGCTGGCTGTGCATT 115 60° C. ◯(1.65) X(0.92) RGACCAGATAGAGAACGCCGA 119 15 A1590053 F GTGAATGCCTCTGGAGTGGT 117 65° C.◯(1.20) X X(0.46) (AL137672) R TTCTGTTCTGACGCCAAGTG 118 16 MAP3K5 FGTTCTAGCCAGTACTTCCGG 119 60° C. ◯(1.64) X(0.69) 0.0528 RACTCGCTCCGAATTCTTGC 120 17 TIMP1 F ATTCCGACCTCGTCATCAGG 121 60° C.◯(2.91) ◯(1.62) R GCTGGTATAAGGTGGTCTGG 122 18 GSTM1 FGGACTTTCCCAATCTGCCCT 123 60° C. ◯(3.19) ◯(1.64) R AGGTTGTGCTTGCGGGCAAT124 19 CSDA F AGGAGAGAAGGGTGCAGAAG 125 60° C. ◯(2.50) X(1.09) RCCTTCCATAGTAGCCACGTC 126 20 GSTM2 F ACAACCTGTGCGGGGAATCA 127  65° C.◯(1.82) X(0.75) R GGTCATAGCAGAGTTTGGCC 129 21 SGK F GCAGAAGGACAGGACAAAGC129  60° C. ◯(1.75) X(0.71) R CAGGCTCTTCGGTAAACTCG 130 22 LMNA FATGGAGATGATCCCTTGCTG 131 60° C. X(1.11) X X(0.50) 0.0202  (opposite) RAGGTGTTCTGTGCCTTCCAC 132 0.0547  (opposite) 23 MGP FGCTCTAAGCCTGTCCACGAG 133 60° C. ◯(3.12) ◯(1.83) R CGCTTCCTGAAGTAGCGATT134 24 LTBP2 F GCGACACAGGAGTGTCAAGA 135 60° C. ◯(2.20) ◯(1.21) RTGACCATGATGTAGCCCTGA 136 With regard to “correspondence withmicroarray,” the ratio of the late recurrence group and the earlyrecurrence group was obtained from the results of quantitative PCR on 4cases used for microarray analysis, and genes with the ratio of 1.5 orgreater were indicated with ◯. X indicates no difference, and X Xindicates an opposite correlation. With regard to “correlation,” genesexhibiting a correlation between the gene expression levels of 10 caseswherein the number of months of recurrence had been determined, and theperiod required for recurrence, were indicated with the r value and thep value. In “significant difference between two groups,” with regard togenes exhibiting a significant difference in expression levels between 6cases of the recurrence within 24 months, and 8 cases of no recurrencefor 48 months or more (the upper case) or 6 cases of no recurrence for60 months or more (the lower case). p values (Mann-Whitney U test) wereindicated.

As a result, it was found that when GAPDH was used as an internalstandard gene, 19 out of the 24 gene candidates exhibiting up-regulationin the late recurrence group corresponded with the microarray results,and that among such genes, no genes exhibited a correlation with therecurrence period. In addition, when 18S rRNA was used as an internalstandard gene, 9 out of the above 24 gene candidates corresponded withthe microarray results, and among them, only 1 gene (PZP gene) exhibiteda correlation with the recurrence period

A significant difference test was carried out on two groups, the laterecurrence group and the early recurrence group. As a result, it wasfound that when GAPDH was used as a standard gene, only one gene (MAP3K5gene) exhibited a significant difference, and that when 18S rRNA wasused as a standard gene, only one gene (TNFSF14 gene) exhibited asignificant difference. On the contrary, there was one gene (LMNA gene),which had a significant difference, oppositely correlating to therecurrence period. Accordingly, this gene was identified as a geneup-regulated in nontumor tissues in the early recurrence group.

Subsequently, the results obtained by analyzing the 47 gene candidates(BNbad) up-regulated in nontumor tissues in the early recurrence groupof type B hepatocellular carcinoma cases are shown in Table 15. Table 15shows the analysis results obtained by quantitative PCR, which wasperformed on the cases shown in Table 13 as targets, under theconditions shown in Table 15 using GAPDH or 18S rRNA as an internalstandard gene.

TABLE 15Results of quantitative PCR of “genes up-regulated in nontumor tissues in early recurrence group of hepatitis B cases”Significant Significant Correspondence Correspondence  differencedifference with microarray, with microarray, between between Forward/Prime SEQ Annealing normalized with normalized with CorrelationCorrelation two groups two groups No. Gene reverse sequence (5-3) ID NO. temperature GAPDH 18S rRNA (GAPDH) (18S rRNA) (GADPH) (18S rRNA)1 CTH F TGAATGGCCACAGTGATGTT 137 60° C. ◯(4.41) ◯(13.25) RCCATTCCGTTTTTGAAATGC 138 2 OAT F TCGTAAGTGGGGCTATACCG 139 60° C. ◯(2.70)◯(11.89) R CTGGTTGGGTCTGTGGAACT 140 3 PRODH F CTGACCACCGGGTGTACTTT 14160° C. ◯(4.61) ◯(22.30) R GACAAGTAGGGCAGCACCTC 142 4 CYP3A7 FGGAACCCGTACACATGGACT 143 60° C. X X(0.39) X (1.27) RAACGTCCAATAGCCCTTACG 144 5 DDT F CGCCCACTTCTTTGAGTTTC 145 60° C. X(1.04)◯(4.42) R CATGACCGTCCCTATCTTGC 146 6 PGRMC1 F TATGGGGTCTTTGCTGGAAG 14765° C. X(1.15) ◯(3.48) R GCCCACGTGATGATACTTGA 148 7 AKR1C1 FGGTCACTTCATGCCTGTCCT 149 60° C. X(1.32) ◯(3.95) R TATGGCGGAAGCCAGCTTCA150 8 HGD F CACAAGCCCTTTGAATCCAT 151 60° C. ◯(1.61) ◯(5.80) RTGTCTCCAGCTCCACACAAG 152 9 FHR4 F TTGAGAATTCCAGAGCCAAGA 153 60vC.X (0.83) ◯(1.85) R CACCCATCTTCACCACACAC 154 10 FST FAAGACCGAACTGAGCAAGGA 155 65° C. ◯(3.58) ◯(6.80) R TTTTTCCCAGGTCCACAGTC156 11 COX4 F — — — — R — 12 APP F CGGGCAAGACTTTTCTTTGA 157 60° C.X(1.28) ◯(4.13) R TGCCTTCCTCATCCCCTTAT 158 13 PSPHL FTCCAAGGATGATCTCCCACT 159 60° C. ◯(4.97) ◯(5.44) R AGCATCCGATTCCTTCTTCA160 14 CYP1A1 F TGATAAGCACGTTGCAGGAG 161 65° C. ◯(2.77) ◯(11.30) 0.0389R AAGTCAGCTGGGTTTCCAGA 162 0.0547 15 ZNF216 F GGTGTCAGAGCCAGTTGTCA 16360° C. ◯(1.84) ◯(5.39) R AAATTTCCACATCGGCAGTC 164 16 LEPR FCCACCATTGGTACCATTTCC 165 60° C. ◯(5.78) ◯(14.99) R CCCCTCACCTGAACCTCATA166 17 TOM1L1 F TTTTCTGGAACATTCAAATTCA 167 60vC. X (0.89) ◯(2.61) RCACTTTTTGTCATCGCTGGA 168 18 PECR F TGCAGTGGAATACGGATCAA 169 60° C.X (1.19) ◯(3.49) R GGAAGCAGACCACAGAGGAG 170 19 ALDH7A1 FAGTGGAAGGTGTGGGTGAAG 171 65vC. X(1.34) ◯(3.45) R CAACCATACACTGCCACAGG172 20 GNMT F CACTTAAGGAGCGCTOGAAC 173 60° C. ◯(1.82) ◯(6.15) RTTTGCAGTCTGGCAAGTGAG 174 21 OATPC F GCCACTTCTGCTTCTGTGTTT 175 60° C.X (1.27) ◯(3.50) R TCCACCATAAAAGATGTGGAAA 176 22 AKR1B10 FCCTCCACTCATGTCCCATTT 177 60° C. ◯(2.92) ◯(8.05) R TCAAGCCATGCTTTTCTGTG178 23 ANGPTL3 F ATTTTAGCCAATGGCCTCCT 179 60° C. X(1.18) ◯(3.37) RCACTGGTTTGCAGCGATAGA 180 24 AASS F ATTGGTGAATTGGGATTGGA 181 60° C.◯(2.04) ◯(6.83) R GAAGCCCACCACAGTAGGAA 182 25 CALR FTGGATCGAATCCAAACACAA 183 60° C. X(1.12) ◯(2.77) R CTGGCTTGTCTGCAAACCTT184 26 BAAT F CTCCATCATCCACCCACTTT 185 60° C. X(1.15) ◯(4.06) RGGAAGGCCAGCAAGTGTAGA 186 27 PMM1 F GCCAGAAAATTGACCCTGAG 187 60° C.X(1.04) ◯(3.53) R CAGCTGCTCAGCGATCTTAC 188 28 RABR FCCCTCATCGTGTCAAGTCAA 189 60° C. X(1.15) ◯(3.78) R AGCATCAAACAGACCCAACC190 29 GLUL F TTGTTTGGCTGGGATAGAGG 191 60° C. X(0.85) ◯(2.41) RGCTCTGTCCGGATAGCTACG 192 30 CSHMT F CCCTACAAGGTGAACCCAGA 193 60° C.X(1.20) ◯(3.33) R GGAGTAGCAGCTGGTTCCTG 194 31 UGT1A3 FTGACAACCTATGCCATTTCG 195 60° C. X(0.89) ◯(3.10) R CCACACAAGACCTATGATAGA196 32 HSPG1 F CTCAAGGATGACGTGGGTTT 197 60° C. X(1.45) ◯(4.17) RGATTTCCTCTGGCCAATFCA 198 33 QPRT F AACTACGCAGCCTTGGTCAG 199 60° C.X(1.24) ◯(3.91) R TGGCAGTTGAGTTGGGTAAA 200 34 DEPP FGATGTTACCAATCCCGTTCG 201 60° C. ◯(2.68) ◯(6.92) R TGGGCTCCTATATGCGGTTA202 35 CA2 F TGCTTTCAACGTGGAGTTTG 203 65° C. ◯(1.73) ◯(4.89) RCCCCATATTTGGTGTTCCAG 204 36 FTHFD F CAAAATGCTGCTGGTGAAGA 205 60° C.X(1.28)  ◯(4.65) R GCCTCTGTCAGCTCAAGGAC 206 37 LAMP1 FGTCGTCAGCAGCCATGTTTA 207 60° C. X X(0.61) ◯(1.97) R GGCAGGTCAAAGGTCATGTT208 38 FKBP1A F GGGATGCTTGAAGATGGAAA 209 90° C. X(0.79) ◯(1.78) RCAGTGGCACCATAGGCATAA 210 39 BNIP3 F GCTCCTGGGTAGAACTGCAC 211 60° C.X(1.00) ◯(2.70) R GCCCTGTTGGTATCTTGTGG 212 40 MAP3K12 FTTGAGGAAATCCTGGACCTG 213 60° C. X X (0.59) ◯(1.52) RTTGAGGTCTCGCACCTTCTT 214 41 ASS F CTGATGGAGTACGCAAAGCA 215 60° C.◯(2.81) ◯(9.16) R CTCGAGAATGTCAGGGGTGT 216 42 ACTB F ACAGAGCCTCGCCTTTGC217 60° C. X(0.74)  ◯(2.04) R CACGATGGAGGGGAAGAC 218 43 PLAB FGAGCTGGGAAGATTCGAACA 219 60° C. ◯(2.57) ◯(5.03) R AGAGATACGCAGGTGCAGGT220 44 ENO1L1 F GAGATCTCGCCGGCTTTAC 221 60° C. X(0.75) ◯(2.14) RCGCGAGAGTCAAAGATCTCC 222 45 IGFBP3 F CAGCTCCAGGAAATGCTAGTG 223 60° C.X(0.86) ◯(2.81) 0.0528() R GGTGGAACTFGGGATCAGAC 224 46 UK114 FGAGGGAAGGCTTAGCCATGT 225 60° C. X(1.11) ◯(3.13) R TTGAAGGGTCCATGCCTATC226 47 ERF1 F GCCTGTAAGTACGGGGACAA 227 60° C. X(1.16) ◯(2.82) RCTCTTCAGCGTTGTGGATGA 228 Although Gene Nos. 22 and 33 are genes commonwith CNbad, different sequences were used as PCR primers for Gene No.22. PCR was carried out on Gene No. 11 using 2 primer sets. However,since stable amplification did not achieved in any case, it was pending.With regard to “correspondence with microarray,” the ratio of the earlyrecurrence group and the late recurrence group was obtained from theresults of quantitative PCR on 4 cases used for microarray analysis, andgenes with the ratio of 1.5 or greater were indicated with ◯. Xindicates no difference, and X X indicates an opposite correlation.There were no genes, which exhibited a correlation between the geneexpression levels of 10 cases, wherein the number of months ofrecurrence had been determined, and the period required for recurrence.In “signficant difference between two groups,” with regard to genesexhibiting a significant difference in expression levels between 6 casesof the recurrence within 24 months, and 6 cases of no recurrence for 48months or more (the upper case) or 6 cases of no recurrence for 60months or more (the lower case). p values (Mann-Whitney U test) wereindicated.

As a result, it was found that when GAPDH was used as an internalstandard gene, 16 gene corresponded with the microarray results, butthat no genes significantly exhibited a correlation with the recurrenceperiod. However, the IGFBP3 gene significantly exhibited an oppositecorrelation in the significant difference test between two groups.Accordingly, this gene was identified as a gene up-regulated in nontumortissues in the late recurrence group.

In addition, when 18S rRNA was used as an internal standard gene, 45genes corresponded with the microarray results, but that no genessignificantly exhibited a correlation with the recurrence period.However, the CYP1A1 gene significantly exhibited a correlation in asignificant difference test between two groups. Accordingly, this genewas identified as a gene up-regulated in nontumor tissues in the earlyrecurrence group.

As stated above, the following 6 genes were identified as genesexpressed in nontumor tissues, which can be used for prediction of therecurrence of cancer in type B hepatocellular carcinoma cases: the PZPgene, the MAP3K5 gene, the TNFSF14 gene, the LMNA gene, the CYP1A1 gene,and the IGFBP3 gene. The meanings of the aforementioned genes are asfollows:

PZP gene: A pregnancy-zone protein geneMAP3K5 gene: A mitogen-activated protein kinase 5 geneTNFSF14 gene: A tumor necrosis factor (ligand) superfamily, member 14geneLMNA gene: A lamin A/C geneCYP1A1 gene: A cytochrome P450, family 1, subfamily A, polypeptide 1geneIGFBP3 gene: An insulin-like growth factor binding protein 3 gene

EXAMPLE 4 Selection of Combination of Genes Used for DistinguishingEarly Recurrence Group from Late Recurrence Group

By combining several genes expressed in nontumor tissues used forprediction of the recurrence of type C or B hepatocellular carcinoma,which were obtained from the results of Examples 2 and 3, it becomespossible to carry out recurrence prediction more precisely. As such genesets, many types of sets are conceived. Examples of the aforementionedcombination are shown in Table 16.

TABLE 16 Examples of combinations of genes used for distinguishinghepatocellular carcinoma early recurrence group from late recurrenceNormalization with Normalization with Causal cancer Early group Lategroup GAPDH 18S rRNA Type C <24 months >40 months VNN1 VNN1hepatocellular MRPL24 CXCL9 cancer GBP1 RALGDS Classification rate  88%100% Type B <24 months >48 months PRODH LMNA hepatocellular LMNA LTBP2cancer MAP3K12 COL1A2 PZP Classification rate 100% 100%

(1) Prediction of Type C Hepatocellular Carcinoma

When GAPDH is used as an internal standard gene for normalization ofgene expression in the distinction of an early recurrence group whereinthe cancer has recurred within 24 months from a late recurrence groupwherein the cancer has not recurred for 40 months or more, the geneexpression level of VNN1 and that of MRPL24 may be examined. Otherwise,when 18S rRNA is used as an internal standard gene for normalization inthe above distinction, the expression level of each gene of a gene setconsisting of VNN1, CXCL9, GBP1, and RALGDS may be examined. Theexpression level of each of the aforementioned genes is assigned to adiscriminant using a discriminant function coefficient obtainedregarding each gene, and the obtained value is used for distinction. Theexpression level of the above gene group is analyzed. In the case ofGAPDH normalization, the classification rate between the earlyrecurrence group and the late recurrence group is found to be 88%, andin the case of 18S rRNA, the classification rate is found to be 100%.

(2) Prediction of Type B Hepatocellular Carcinoma

When GAPDH is used as an internal standard gene for normalization in thedistinction of an early recurrence group wherein the cancer has recurredwithin 24 months from a late recurrence group wherein the cancer has notrecurred for 48 months or more, the expression level of each gene of agene set consisting of PRODH, LMNA, and MAP3K12 may be examined.Otherwise, when 18S rRNA is used as an internal standard gene fornormalization in the above distinction, the expression level of eachgene of a gene set consisting of LMNA, LTBP2, COL1A2, and PZP may beexamined. As described above, such expression levels are assigned to adiscriminant, and the obtained values are used for distinction. Theexpression level of the above gene group is analyzed. In both cases ofcorrelation with GAPDH and 18S rRNA, the classification rate between theearly recurrence group and the late recurrence group is found to be100%.

The meanings of the aforementioned genes are as follows:

PRODH gene: A proline dehydrogenase (oxidase) 1 geneLTBP2 gene: A latent transforming growth factor beta binding protein 2geneCOL1A2 gene: A collagen, type I, alpha 1 geneMAP3K12 gene: A mitogen-activated protein kinase 12 gene

INDUSTRIAL APPLICABILITY

By identifying common genes derived from a patient and a healthy subjectand cause-specific genes, it becomes possible to predict prognosis andrecurrence. Accordingly, the thus identified genes can be used fordiagnosis, the development of treatment methods, and a strategy ofselecting a therapeutic agent (Taylor-made medicine).

SEQUENCE LISTING FREE TEXT

SEQ ID NOS: 1 to 228: synthetic DNA

1. A method for evaluating cancer, which comprises the following stepsof: (a) collecting total RNA from an analyte; (b) measuring theexpression level of at least one gene selected from among the genesshown in Tables 1 to 8; and (c) evaluating cancer using the measurementresult as an indicator.
 2. A method for evaluating cancer, whichcomprises the following steps of: (a) collecting total RNA from ananalyte; (b) measuring the expression level of at least one geneselected from the group consisting of the PSMB8 gene, the RALGDS gene,the GBP1 gene, the RPS14 gene, the CXCL9 gene, the DKFZp564F212 gene,the CYP1B1 gene, the TNFSF10 gene, the NROB2 gene, the MAFB gene, theBF530535 gene, the MRPL24 gene, the QPRT gene, the VNN1 gene, and theIRS2 gene; and (c) evaluating cancer using the measurement result as anindicator.
 3. A method for evaluating cancer, which comprises thefollowing steps of: (a) collecting total RNA from an analyte; (b)measuring the expression level of at least one gene selected from thegroup consisting of the PZP gene, the MAP3K5 gene, the TNFSF14 gene, theLMNA gene, the CYP1A1 gene, and the IGFBP3 gene; and (c) evaluatingcancer using the measurement result as an indicator.
 4. A method forevaluating cancer, which comprises the following steps of: (a)collecting total RNA from an analyte; (b) measuring the expression levelof each gene contained in a gene set consisting of the VNN1 gene and theMRPL24 gene, or a gene set consisting of the PRODH gene, the LMNA gene,and the MAP3K12 gene, using GAPDH as an internal standard gene; and (c)evaluating cancer using the measurement result as an indicator.
 5. Amethod for evaluating cancer, which comprises the following steps of:(a) collecting total RNA from an analyte; (b) measuring the expressionlevel of each gene contained in a gene set consisting of the VNN1 gene,the CXCL9 gene, the GBP1 gene, and the RALGDS gene, or a gene setconsisting of the LMNA gene, the LTBP2 gene, the COL1A2 gene, and thePZP gene, using 18S rRNA as an internal standard gene; and (c)evaluating cancer using the measurement result as an indicator.
 6. Themethod according to any one of claims 1 to 5, wherein the evaluation ofcancer involves prediction of the presence or absence of metastasis orrecurrence.
 7. The method according to any one of claims 1 to 5, whereinthe cancer is hepatocellular carcinoma.
 8. The method according to claim2 or 3, wherein the expression level of a gene can be measured byamplifying the gene, using at least one set of primers consisting of thenucleotide sequences shown in SEQ ID NOS: 2n−1 and 2n (wherein nrepresents an integer between 1 and 114).
 9. The method according toclaim 4 or 5, wherein the expression level of a gene can be measured byamplifying the gene, using a set of primers for amplifying each genecontained in at least one gene set selected from the group consisting ofa gene set consisting of the VNN1 gene and the MRPL24 gene, a gene setconsisting of the PRODH gene, the LMNA gene, and the MAP3K12 gene, agene set consisting of the VNN1 gene, the CXCL9 gene, the GBP1 gene, andthe RALGDS gene, and a gene set consisting of the LMNA gene, the LTBP2gene, the COL1A2 gene, and the PZP gene.
 10. A primer set, whichcomprises at least one set of primers consisting of the nucleotidesequences shown in SEQ ID NOS: 2n−1 and 2n (wherein n represents aninteger between 1 and 114).
 11. A primer set, which comprises a set ofprimers for amplifying each gene contained in at least one gene setselected from the group consisting of a gene set consisting of the VNN1gene and the MRPL24 gene, a gene set consisting of the PRODH gene, theLMNA gene; and the MAP3K12 gene, a gene set consisting of the VNN1 gene,the CXCL9 gene, the GBP1 gene, and the RALGDS gene, and a gene setconsisting of the LMNA gene, the LTBP2 gene, the COL1A2 gene, and thePZP gene.
 12. A kit for evaluating cancer, which comprises any geneshown in Tables 1 to
 8. 13. A kit for evaluating cancer, which comprisesat least one gene selected from the group consisting of the RALGDS gene,the GBP1 gene, the DKFZp564F212 gene, the TNFSF10 gene, and the QPRTgene.
 14. A kit for evaluating cancer, which comprises each genecontained in at least one gene set selected from the group consisting ofa gene set consisting of the VNN1 gene and the MRPL24 gene, a gene setconsisting of the PRODH gene, the LMNA gene, and the MAP3K12 gene, agene set consisting of the VNN1 gene, the CXCL9 gene, the GBP1 gene, andthe RALGDS gene, and a gene set consisting of the LMNA gene, the LTBP2gene, the COL1A2 gene, and the PZP gene.
 15. The kit according to anyone of claims 12 to 14, which further comprises the primer set accordingto claim 10 or 11.